Application of Artificial Intelligent in the Prediction of Consumer Behavior from Facebook Posts Analysis

Abstract—The undeniable fact is that online business today
has increased at a very fast pace everywhere around the globe.
This happens through the widely used of Social Media,
especially Facebook which is the most popular platform in the
world. It would be really useful for the digital marketers, if
there is a certain tool that can predict the intentions of the web
patrons when the brand is posting the message to communicate
with their fans or followers.
The aim of this research is to develop an analytic tool which
can support online vendors to predict behaviors of the patrons
according to Dentsu’s AISAS perspective. An Artificial
intelligent model was developed by the results from 75
specialists who evaluated the behavior that will likely occur
after the comments have been posted. The results, hence, were
collected and prepared for the data modelling process using the
Naïve Bayes probability concept, afterwards, testing for the
model’s accuracy with 10-fold cross validation technique. As the
previous study indicated, Naïve Bayes technique gives the best
result for the behavior analysis, which is also true with this
study. The predictive model for AISAS behavior from this study
can give average accuracy higher than 86 percent.
When bringing the AISAS Model to test with 30 live users
who are online vendors, we can conclude that the overall results
of model have been greatly appreciated and effectively satisfied.
Most vendors also agreed on the ease of use, which creates high
chances of business opportunities.